{"id":"W3038473140","doi":"10.1016/j.mri.2020.01.001","title":"Comparison of DCE-MRI parametric mapping using MP2RAGE and variable flip angle T1 mapping","year":2020,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba; CancerCare Manitoba","funders":"University of Manitoba","keywords":"Flip angle; Magnetic resonance imaging; Imaging phantom; Nuclear medicine; Multiparametric MRI; Biomedical engineering; Nuclear magnetic resonance; Medicine; Prostate; Radiology; Physics; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001357942,0.0001743003,0.0004486317,0.0001471378,0.0001165638,0.0000297373,0.0001160848,0.00004670584,0.00005740405],"category_scores_gemma":[0.0001350359,0.0001801326,0.00005070123,0.00105212,0.0001250972,0.0001075249,0.0001239217,0.000234987,0.000004356687],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004977395,"about_ca_system_score_gemma":0.00004635898,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005805214,"about_ca_topic_score_gemma":2.986196e-7,"domain_scores_codex":[0.9986023,0.00002254853,0.0004561538,0.0003946034,0.0002112365,0.0003131514],"domain_scores_gemma":[0.9992151,0.00008812606,0.0001696143,0.0002875139,0.00009229349,0.0001474086],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008154941,0.0002692245,0.2793233,0.0006538697,0.00001141926,0.00005020167,0.002221637,0.001371217,0.2526567,0.003266997,0.002303156,0.4577908],"study_design_scores_gemma":[0.001521186,0.0002264143,0.04572481,0.0008547951,0.00009823715,0.00009682735,0.001712625,0.7155464,0.009878151,0.00123889,0.222616,0.0004857449],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1757175,0.03030061,0.7875487,0.002095609,0.00004044515,0.0008551485,0.00001618057,0.000219947,0.003205879],"genre_scores_gemma":[0.5963335,0.0001995686,0.4026725,0.0005466696,0.00007960932,0.00002498226,0.000007804452,0.0000285717,0.0001067693],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7141752,"threshold_uncertainty_score":0.7345594,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05354340258618417,"score_gpt":0.3361356909430994,"score_spread":0.2825922883569152,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}